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Qwen3 VL 32B (Reasoning)

AlibabaQwenオープンウエイトApache 2.0 · 商用利用可

説明

Qwen3-VL is a large multimodal model that unifies vision, language, and reasoning to achieve human-level perception and cognition across text, images, and video. Built on a 235B-parameter architecture, it integrates early joint training of visual and textual modalities for strong language grounding. The model supports up to a 1 million-token context window and excels at visual understanding, spatial reasoning, long video comprehension, and tool-based interaction. It can generate code from images, perform precise 2D/3D object grounding, and operate digital interfaces like a visual agent. The “Instruct” version rivals Gemini 2.5 Pro in perception benchmarks, while the “Thinking” version leads in multimodal reasoning and STEM tasks. With multilingual OCR, creative writing, and fine-grained scene interpretation, Qwen3-VL establishes a new open-source frontier for integrated vision-language intelligence.

リリース日
2025-10-21
パラメータ
33.0B
コンテキスト長
131K
モダリティ
image, text

能力レーダー

36
general
64
coding
83
reasoning
45
science
70
agents
90
multimodal

ランキング

ドメイン#順位スコアソース
エージェント能力57
51.0
LS
コーディングランキング213
53.0
AA
総合ランキング231
52.0
AA
マルチモーダルランキング23
60.0
LS
科学295
46.0
AA

ベンチマークスコア (LLM Stats)

(LLM Stats (zeroeval))

3d

BLINK68.5%自己申告

Agents

BFCL-v371.7%自己申告
AndroidWorld_SR63.7%自己申告
OSWorld41.0%自己申告

Biology

GPQANYU + Cohere + Anthropic (2023)73.1%自己申告

Chemistry

SuperGPQA59.0%自己申告

Communication

MM-MT-Bench8.30 / 100自己申告
WritingBench86.2%自己申告
Multi-IF78.0%自己申告

Creativity

Creative Writing v383.3%自己申告
Arena-Hard v260.5%自己申告

Factuality

SimpleQA55.4%自己申告

Finance

MMLU88.7%自己申告
MMLU-Pro82.1%自己申告
MMLU-ProX77.2%自己申告

General

MMLU-Redux91.9%自己申告
IFEvalGoogle Research (2023)87.8%自己申告
MMStar79.4%自己申告
MMMU (val)78.1%自己申告
Include76.3%自己申告
LiveBench 2024112574.7%自己申告
MMMU-Pro68.1%自己申告
LiveCodeBench v665.6%自己申告

Grounding

ScreenSpot95.7%自己申告
ScreenSpot Pro57.1%自己申告

Healthcare

VideoMMMU79.0%自己申告

Image To Text

OCRBench85.5%自己申告
OCRBench-V2 (en)68.4%自己申告
OCRBench-V2 (zh)62.1%自己申告

Language

CharadesSTA62.8%自己申告

Long Context

LVBench62.6%自己申告

Math

MathVista-Mini85.9%自己申告
AIME 202583.7%自己申告
MathVision70.2%自己申告
PolyMATH52.0%自己申告

Multimodal

DocVQAtest96.1%自己申告
MMBench-V1.190.8%自己申告
CharXiv-D90.2%自己申告
InfoVQAtest89.2%自己申告
AI2D88.9%自己申告
MuirBench80.3%自己申告
VideoMME w/o sub.77.3%自己申告
MVBench73.2%自己申告
CharXiv-R65.2%自己申告

Reasoning

Hallusion Bench67.4%自己申告
ERQA52.3%自己申告

Spatial Reasoning

RealWorldQA78.4%自己申告

AA評価指数

(Artificial Analysis)
Math Index(Artificial Analysis)
84.7
Intelligence Index(Artificial Analysis)
18.1
Aime 25(MAA (Mathematical Association of America))
0.8
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
0.8
Livecodebench(UC Berkeley + MIT + Cornell (2024))
0.7
Gpqa(NYU + Cohere + Anthropic (2023))
0.7
Ifbench(Google Research (2023))
0.6
Lcr(Artificial Analysis)
0.6
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.5
Scicode(UIUC + Argonne National Lab (2024))
0.3
Hle(Center for AI Safety + Scale AI (2025))
0.1
Terminalbench Hard(Stanford × Laude Institute (2026))
0.1

LLM Statsカテゴリスコア

(LLM Stats (zeroeval))
Communication
3
Multimodal
1
General
90
Legal
80
Math
80
Structured Output
80
Instruction Following
80
Language
80
Finance
80
Grounding
80
Healthcare
80
Creativity
80
Writing
80
Physics
70
Reasoning
70
Spatial Reasoning
70
Image To Text
70
3d
70
Biology
70
Chemistry
70
Tool Calling
70
Video
70
Vision
70
Long Context
60
Factuality
60
Agents
60
Economics
60

価格設定

入力価格$0.7 / 1Mトークン
出力価格$8.4 / 1Mトークン
混合価格(3:1)$2.625 / 1Mトークン

速度

トークン/秒0.0
初トークン遅延0.00s
初回答遅延0.00s

プロバイダー価格ランキング

プロバイダー価格ランキング

3 プロバイダー

最安: OpenRouter最高: Alibaba
プロバイダー入力出力
1OpenRouter最安
$0.104
$0.416
2Kilo Gateway
$0.104
$0.416
3Alibabaプライマリ
$0.7
$8.4

このモデルの異なるAPIプロバイダー間の価格を比較。

外部リンク